Side-by-side comparison
Kimi K2.6 vs Qwen3.6 27B
MoonshotAI
Kimi K2.6
👁 Vision
🔧 Tools
{} JSON
Input / 1M
$0.7300
Output / 1M
$3.4900
| Kimi K2.6 | Qwen3.6 27B | |
|---|---|---|
| Provider | MoonshotAI | Qwen |
| Context window Maximum tokens (input + output) the model can process in a single request. Glossary → | 262,142 | 262,144 |
| Capabilities Optional capabilities the model advertises: vision (images), tools (function calling), json_mode (structured output). | vision, tools, json_mode | vision, tools, json_mode |
| Input $ / 1M tokens Cost for tokens you send (prompt + context). Cheaper side highlighted. Glossary → | 0.7300 | 0.3200 |
| Output $ / 1M tokens Cost for tokens the model generates. Output is normally 3–5× pricier than input. Glossary → | 3.4900 | 3.2000 |
Frequently asked questions
Which is cheaper, Kimi K2.6 or Qwen3.6 27B?
Qwen3.6 27B is cheaper than Kimi K2.6 on a 50/50 input/output blend by about $0.35 per 1M tokens. Exact savings depend on your input-vs-output ratio — use the cost calculator on this page for a workload-specific estimate.
Which has a larger context window, Kimi K2.6 or Qwen3.6 27B?
Qwen3.6 27B has the larger context window at 262k tokens versus 262k tokens for Kimi K2.6. That means Qwen3.6 27B can ingest about 1.0x as much text per request.
What is the difference between Kimi K2.6 and Qwen3.6 27B?
Kimi K2.6 comes from MoonshotAI; Qwen3.6 27B comes from Qwen. They differ in pricing, context window, and supported capabilities — see the side-by-side table on this page for the exact figures, refreshed nightly.